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Monitoring Motor Symptoms in Parkinson’s Disease Under Long Term Acoustic Stimulation

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Artificial Intelligence in Neuroscience: Affective Analysis and Health Applications (IWINAC 2022)

Abstract

Parkinson’s disease (PD) is a progressive neurodegenerative disease that presents motor (tremor, rigidity, bradykinesia, and instability) and non-motor dysfunctions. In this study we present a methodology to monitor the evolution of motor symptoms of Parkinson disease patients remotely, and its application to asses the effects of an experimental therapeutic intervention based on acoustic stimulation in a two months’ study. Monitoring is based on wearing a commercial smartwatch while performing a set of exercises extracted from the Unified Parkinson’s Disease Rating Scale. Three indicators are extracted from the triaxial accelerometer’s signals to monitor tremor and bradykinesia. Results of the evolution of these indicators over a 2 months’ study are shown for two PD patients following a therapeutic intervention based on acoustic stimulation and a healthy control group of similar age and gender. The feasibility of using consumer smartwatches for remote monitoring of motor symptom’s is discussed together with its limitations, specially regarding long-term assessment of acoustic stimulation interventions.

Supported by Instrumentation and applied acoustics research group.

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Acknowledgements

This work has been funded by grant TECA-PARK_55_01 under the POCTEP 0348_CIE_6_E program of Fundacion General del CSIC. The authors would like to thank the Parkinson’s associations of Madrid, Valladolid, Burgos, Asturias, Jovellanos and Hogar Santa Estefânia de Guimaraes for their participation in this study, and also to Dr. J. C. Martiınez-Castrillo, Dr. M. Gago and Dra. M. Blazquez for their contributions and continuous support.

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Correspondence to G. de Arcas .

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Sigcha, L., Gonzalez Calleja, D., Pavón, I., López, J., de Arcas, G. (2022). Monitoring Motor Symptoms in Parkinson’s Disease Under Long Term Acoustic Stimulation. In: Ferrández Vicente, J.M., Álvarez-Sánchez, J.R., de la Paz López, F., Adeli, H. (eds) Artificial Intelligence in Neuroscience: Affective Analysis and Health Applications. IWINAC 2022. Lecture Notes in Computer Science, vol 13258. Springer, Cham. https://doi.org/10.1007/978-3-031-06242-1_19

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  • DOI: https://doi.org/10.1007/978-3-031-06242-1_19

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-031-06242-1

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